End of training

README.md

@@ -3,11 +3,6 @@ license: apache-2.0
 base_model: distilbert/distilbert-base-uncased
 tags:
 - generated_from_trainer
-metrics:
-- accuracy
-- precision
-- recall
-- f1
 model-index:
 - name: spam
   results: []
@@ -19,12 +14,6 @@ should probably proofread and complete it, then remove this comment. -->
 # spam
 
 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.6940
-- Accuracy: 0.4954
-- Precision: 0.2454
-- Recall: 0.4954
-- F1: 0.3282
 
 ## Model description
 
@@ -43,20 +32,19 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2
+- learning_rate: 2e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| No log        | 1.0   | 256  | 0.7098          | 0.5046   | 0.2546    | 0.5046 | 0.3384 |
-| 13078.501     | 2.0   | 512  | 0.6940          | 0.4954   | 0.2454    | 0.4954 | 0.3282 |
+| No log        | 1.0   | 256  | 0.0107          | 0.9985   | 0.9985    | 0.9985 | 0.9985 |
 
 
 ### Framework versions